Good decisions need clean data and people who understand what it means. Our data analysts and data engineers have built reporting, forecasting and data platforms inside large banks, card issuers, mortgage companies and fintechs. They work in SQL, Python, SAS, Tableau, Snowflake, Databricks and AWS, and they join your team ready to work in your data from the first week.
Data analytics
- Reporting, dashboards and data visualization in Tableau, Power BI and Looker
- Forecasting, and KPI and metrics design
- Customer segmentation
- A/B testing, champion/challenger and test-and-learn programs
- Root-cause and deep-dive analysis
- Data quality and validation
- Ad hoc analysis for executives and business teams
Data engineering
- Data pipelines and ETL/ELT
- Data warehouses, data lakes and data marts
- Cloud migrations to AWS, Azure, Google Cloud and Databricks
- Automation of manual data and reporting processes
- Data governance, data lineage and metadata management
- API integration
- Platform consolidation and cost reduction
Tools our consultants use
- Languages: SQL, Python, R and SAS
- Visualization: Tableau, Power BI, Looker and Qlik
- Data platforms: Snowflake, Databricks, Teradata, Oracle and SQL Server
- Cloud: AWS, Azure and Google Cloud (BigQuery)
- Big data and engineering: Hadoop, Spark, Hive, dbt, Airflow, Git and Alteryx
- Excel and VBA for fast, practical analysis
Roles we place
- Data analysts and senior data analysts
- Data scientists
- Data engineers
- BI and reporting developers
- Analytics managers and directors
Examples from our consultants' careers
Work our consultants did before or alongside Augment, described without naming employers or clients.
- Moved 20+ front-line management reports off manual processes onto governed data marts and Tableau at a top 10 US bank, as part of a consent-order response.
- Migrated a large bank’s home-lending finance data from on-premise SQL Server to Databricks on AWS, more than halving the daily pricing-report cycle.
- Built an end-to-end AWS data platform automating pipelines over about 2 billion rows of agency mortgage performance data.
- Designed a plan to consolidate a bank’s five data platforms to two by moving analytic data to the cloud, cutting projected operating cost from $20 million to $8 million a year.
- Led a 40+ person team of data engineers, analysts and data scientists through a cloud migration and analytical data-warehouse build for a large bank’s CFO organization.
- Ran eight A/B tests and a difference-in-differences study for a payments company, showing 3% to 13% conversion gains.
- Rebuilt collections reporting for a financial services firm, improving forecast accuracy 15% and cutting executive report volume 40%.
Recent Augment work
- Supported Phase 1 of a large reporting project through a partner consultancy.
Frequently asked questions
How quickly can you start?
We can usually share consultant profiles the same day we first speak with you. Most consultants start 2 to 4 weeks after that first conversation, and our fastest start so far was 2 business days. We can move at your pace. More answers in our FAQ.
Which tools do your data consultants use?
The most common are SQL, Python, Tableau, AWS, Excel, R, SAS, Snowflake and Power BI, followed by Oracle, Databricks, Hadoop and Spark. Tell us your stack and we will match consultants who have worked in it.
How is pricing set?
Each consultant sets their own hourly rate and Augment adds a transparent margin. We aim to keep our gross margin at about 20%, well below traditional consultancies. You see each consultant’s billable rate on their resume before you interview.
Need analytics or risk talent?
Tell us what you need. We can usually share consultant profiles the same day. Read our FAQ.